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apify-competitor-intelligence

Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.

72

3.10x
Quality

61%

Does it follow best practices?

Impact

90%

3.10x

Average score across 3 eval scenarios

SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/apify-competitor-intelligence/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

57%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is well-organized and mostly lean with concrete, runnable commands, but it is held back by a missing bundle script, a vague parameter step, and the absence of validation checkpoints in a batch-extraction workflow.

Suggestions

Add an explicit validation checkpoint to the workflow (e.g., after Step 2 confirm the schema returned, after Step 4 verify the output file is non-empty) with a fix-and-retry loop.

Resolve the missing reference: either bundle reference/scripts/run_actor.js in the skill or replace the command with self-contained, inline executable steps.

Make Step 3 concrete by specifying default result counts per use case instead of "Based on character of use case".

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence, with no padding or explanations of concepts Claude already knows; the large Actor-selection table is actionable reference data rather than fluff, leaving only minor tightening opportunities, so it sits above the midpoint but below a perfectly lean 5.

4 / 5

Actionability

Provides concrete bash commands with real Actor IDs and copy-paste flags (--actor, --input, --output, --format), but Step 4's commands reference ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js which is not present in the bundle, and Step 3's "Number of results: Based on character of use case" is vague, leaving key execution details incomplete.

3 / 5

Workflow Clarity

A clear 5-step checklist sequences the process, but this is a batch data-extraction operation with no explicit validation/verification checkpoint (e.g., confirm the schema fetch succeeded, verify output non-empty) or validate-fix-retry loop, so per the batch-operation cap workflow clarity cannot exceed 3.

3 / 5

Progressive Disclosure

The single SKILL.md is organized into clear sections but the only external reference (run_actor.js) is buried inside a bash command rather than clearly signaled, and no references/scripts/assets bundle files exist, so structure is present but not well split or navigable.

3 / 5

Total

13

/

20

Passed

Description

66%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description clearly conveys what the skill does and targets a distinctive, well-scoped niche, but it lacks an explicit "Use when..." trigger clause, which caps its completeness and limits its overall quality.

Suggestions

Add an explicit trigger clause such as "Use when the user wants to benchmark or compare competitors across maps, booking, social, or video platforms."

Include common user phrasings like "competitor analysis" or "benchmark competitors" to improve trigger-term coverage.

Tighten abstract terms ("strategies", "positioning") into more concrete actions (e.g., "compare pricing, scrape reviews, track ad creatives").

DimensionReasoningScore

Specificity

Names the competitor-intelligence domain and enumerates several concrete analysis targets ("strategies, content, pricing, ads, and market positioning") across seven named platforms, but terms like "strategies" and "positioning" stay somewhat abstract, so it falls just below the comprehensive anchor 5.

4 / 5

Completeness

The "what" is clearly stated (analyze competitor strategies/content/pricing/ads/positioning across platforms) but there is no "Use when..." clause or equivalent explicit trigger guidance, so per the rubric completeness is capped at 3.

3 / 5

Trigger Term Quality

Includes natural platform names users actually say (Google Maps, Booking.com, Facebook, Instagram, YouTube, TikTok) plus "pricing" and "ads", but omits common phrasings like "competitor analysis" or "benchmark competitors", leaving a few natural terms missing.

4 / 5

Distinctiveness Conflict Risk

The competitor-intelligence framing combined with the specific platform list gives it a clear niche with minimal conflict risk, though a broad "Analyze competitor..." opening could lightly overlap with general analysis skills, keeping it just under anchor 5.

4 / 5

Total

15

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
sickn33/agentic-awesome-skills
Reviewed

Table of Contents

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